code: def get_config(self):
      config = super().get_config()
      config["use_batch_norm"] = self.use_batch_norm
      config["num_torch_layers"] = self.num_torch_layers
      return config
  
imports: import os
  import numpy
  import pytest
  import torch
  from absl.testing import parameterized
  from keras import backend
  from keras import layers
  from keras import models
  from keras import saving
  from keras import testing
  from keras.utils.torch_utils import TorchModuleWrapper
label_desc: Use image node_id 3 for calling the Classifier obj's underlying member method code with example usage: obj.get_config() and returns: config